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cs.RO2026
NIDAR: NIR-Guided Intrinsic Decomposition for Scalable Scene-Agnostic LiDAR Intensity Reconstruction
Junjie Zhang, Jie Yin, Kefei Qian +5
LiDAR return intensity provides complementary surface-response cues for robotic perception and state estimation, yet many simulation pipelines omit it or reproduce it using reconst…
cs.RO2026
FastDSAC: Enhancing Policy Plasticity via Constrained Exploration for Scalable Humanoid Locomotion
Guanchen Lu, Yajuan Dun, Yi Zhou +4
Scalable reinforcement learning has popularized high-throughput sampling architectures, which significantly compresses the training time for off-policy methods in robotic locomotio…
cs.RO2026
RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation
Qi Lan, Yining Tang, Yu Shen +4
Safety-critical traffic scenario generation is essential for evaluating autonomous driving systems under rare but high-risk interactions. Existing diffusion-based methods offer str…